1. Technical Field
The present invention relates to a method of computing a disparity, a method of synthesizing an interpolation view, a method of encoding and decoding multi-view video using the same, and an encoder and a decoder using the same. In particular, the present invention relates to a method of computing a disparity, a method of synthesizing an interpolation view, a method of encoding and decoding multi-view video using the same, and an encoder and a decoder using the same, which can rapidly compute an initial disparity of a block using region segmentation, accurately compute a disparity of the block using a variable block, and synthesize an interpolation view on the basis of a disparity value computed in a pixel basis using an adaptive search range, thereby improving quality of the interpolation view, and also can encode and decode a multi-view video independently from an existing prediction mode while using the interpolation view as a reference picture, thereby improving coding efficiency.
2. Related Art
The multi-view video technology is a new video technology that geometrically corrects and spatially combines images at different viewpoints captured by two or more cameras, thereby providing a user with various types of images. The multi-view video technology can provide the user with an image at a specified viewpoint, and can also enable the user to feel a three-dimensional effect through a wide screen. In this case, however, the amount of data to be transmitted is increased in proportion to the number of viewpoints. Accordingly, a method that can efficiently perform coding is needed. In order to solve this problem, MPEG/JVT is at present in the standardization for multi-view video coding (MVC) that can efficiently perform coding using inter-view correlation of multi-view video.
Of these, a coding scheme for view prediction generates an image having high correlation with a screen to be coded using images at neighboring viewpoints and uses the generated image in coding. As the method of synthesizing a picture at an intermediate viewpoint (hereinafter, referred to as “interpolation view”), there are known a technology that uses view warping, and a technology that uses a video interpolation method.
The view warping method generates an intermediate image using a depth image. This method can be applied when internal and external information of the cameras and accurate depth information are secured. With this method, during multi-view video coding, the depth information is also transmitted, and thus additional bit allocation is required. In addition, according to this method, since an effective interpolation view cannot be generated if the internal and external information of the cameras are not provided, an additional work to acquire the camera information is required.
The technology using the video interpolation method generates an interpolation view using a disparity in a pixel basis between the reference pictures. The video interpolation method that has been proposed until now measures the disparity in a pixel basis using block matching. Since the existing methods measure the disparity by setting a maximum disparity, like stereo matching, it is important to accurately apply the maximum disparity in measuring the prediction disparity. In case of an image having many motions, however, it is difficult to predict the motion of an object, and since the maximum disparity may be freely changed, it is difficult to predict an optimum maximum disparity. Accordingly, the above methods have a problem in that image quality is significantly changed according to how the maximum disparity is set. In addition, since the existing methods measure the disparity in a pixel basis using a fixed block, many errors occur in measuring the disparity. Particularly, an error may spread at a boundary of an object having large motion, that is, at a disparity discontinuity, and then the shape of the object having a large disparity may be distorted.
Meanwhile, the synthesized interpolation view may be used for multi-view video coding. To this end, the existing method simply adds the interpolation view to a list of reference pictures. If so, the interpolation view according to the related art has quality inferior to an original picture used for synthesis. For this reason, the interpolation view is rarely used as a reference picture during multi-view video coding, and it may increase an error rate and degrade the coding efficiency, if used.